Computational Complexity and Human Decision-Making

2017 ◽  
Vol 21 (12) ◽  
pp. 917-929 ◽  
Author(s):  
Peter Bossaerts ◽  
Carsten Murawski
2018 ◽  
Author(s):  
Juan Pablo Franco ◽  
Nitin Yadav ◽  
Peter Bossaerts ◽  
Carsten Murawski

Life presents us with decisions of varying degrees of difficulty. Many of them are NP-hard, that is, they are computationally intractable. Two important questions arise: which properties of decisions drive extreme computational hardness and what are the effects of these properties on human-decision making? Here, we postulate that we can study the effects of computational complexity on human decision-making by studying the mathematical properties of individual instances of NP-hard problems. We draw on prior work in computational complexity theory, which suggests that computational difficulty can be characterized based on the features of instances of a problem. This study is the first to apply this approach to human decision-making. We measured hardness, first, based on typical-case complexity (TCC), a measure of average complexity of a random ensemble of instances, and, second, based on instance complexity (IC), a measure that captures the hardness of a single instance of a problem, regardless of the ensemble it came from. We tested the relation between these measures and (i) decision quality as well as (ii) time expended in a decision, using two variants of the 0-1 knapsack problem, a canonical and ubiquitous computational problem. We show that participants expended more time on instances with higher complexity but that decision quality was lower in those instances. These results suggest that computational complexity is an inherent property of the instances of a problem, which affect human and other kinds of computers.


2021 ◽  
Author(s):  
Juan Pablo Franco ◽  
Karlo Doroc ◽  
Nitin Yadav ◽  
Peter Bossaerts ◽  
Carsten Murawski

The survival of human organisms depends on our ability to solve complex tasks, which is bounded by our limited cognitive capacities. However, little is known about the factors that drive complexity of the tasks humans face and their effect on human decision-making. Here, using insights from computational complexity theory, we quantify computational hardness using a set of task-independent metrics related to the computational requirements of individual instances of a task. We then examine the relation between those metrics and human behavior and find that these metrics predict both performance and effort allocation in three canonical cognitive tasks in a similar way. Our findings demonstrate that the ability to solve complex tasks can be predicted from generic metrics of their inherent computational hardness.


2013 ◽  
Author(s):  
Scott D. Brown ◽  
Pete Cassey ◽  
Andrew Heathcote ◽  
Roger Ratcliff

2019 ◽  
Vol 63 (1) ◽  
pp. 105-116
Author(s):  
Mark W. Hamilton

Abstract The dual endings of Hosea promoted reflection on Israel’s history as the movement from destruction to restoration based on Yhwh’s gracious decision for Israel. It thus clarifies the endings of the prior sections of the book (chs. 3 and 11) by locating Israel’s future in the realm of Yhwh’s activities. The final ending (14:10) balances the theme of divine agency in 14:2–9 with the recognition of human decision-making and moral formation as aspects of history as well. The endings of Hosea thus offer a good example of metahistoriography, a text that uses non-historiographic techniques to speak of the movements of history.


2012 ◽  
Author(s):  
Paolo Grigolini ◽  
Bruce J. West

Author(s):  
Nelson Mauro Maldonato ◽  
Alessandro Chiodi ◽  
Donatella di Corrado ◽  
Antonietta M. Esposito ◽  
Salvatore de Lucia ◽  
...  

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